A computational analysis of the apprehension of spatial relations

By Gordon D. Logan, D. D. Sadler. 1996

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A simple neural network module for relational reasoning (2017, background): “d on either rule-based spatial representations or hand-engineered spatial features [8, 10, 20, 21, 24, 29, 38, 39]. Although there are some attempts to learn spatial relations using spatial templates [28, 30], these approaches are less versatile than ours. Visual question answering Visual question a”
A Pooling Approach to Modelling Spatial Relations for Image Retrieval and Annotation (2014, methodology): “Apart from building spatial representations in machine perception, there is a long standing interest from psychologists in und rstanding how hum n appr hend sp tial concepts [20, 26].”
Parallels between spatial cognition and spatial language: Evidence from Williams syndrome (2005, background): “This priming was observed to operate along the entire axis of the reference frame, including both endpoints, even though only one end had been primed (see also Logan & Sadler, 1996).”